/** 使用示例 读取模型，识别CT局部病变 */
public void test2() {
try {
// 实例化ObjectInputStream对象
/*ObjectInputStream ois = new ObjectInputStream(App.class.getResourceAsStream("RandomForest"));*/
ObjectInputStream ois = new ObjectInputStream(new FileInputStream("conf/RandomForest"));
try {
// 读取对象people,反序列化
RandomForest randomForest = (RandomForest) ois.readObject();
ImageFeature imageFeature = new ImageFeature();
/** 图像局部特征提取,参数：图象文件路径，划取区域坐标(x1,y1),(x2,y2) 返回:图像特征向量 */
double[] data =
imageFeature.getFeature(
App.class.getClassLoader().getResource("IMG-0002-00011.jpg").getFile(),
0,
0,
125,
125);
/** 识别算法调用 参数：图像特征向量 返回：病变类型(int型)，1:正常;2:肝癌;3:肝血管瘤;4:肝囊肿;5:其他 */
int type = randomForest.predictType(data);
System.out.println("RandomForest predict:" + type);
} catch (ClassNotFoundException e) {
e.printStackTrace();
}
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
/** 识别模型生成 */
public void testGenerateModel() {
Connection c = null;
Statement stmt = null;
List<Double[]> samples = null;
RandomForest randomforest = null;
try {
Class.forName("org.sqlite.JDBC");
c =
DriverManager.getConnection(
"jdbc:sqlite:/Users/macbook/Documents/IdeaProject/BlackHole/db/cad");
stmt = c.createStatement();
ResultSet rs = stmt.executeQuery("select * from feature");
samples = new ArrayList<Double[]>(rs.getRow());
while (rs.next()) {
Double[] d = new Double[27];
d[0] = rs.getDouble("f1");
d[1] = rs.getDouble("f2");
d[2] = rs.getDouble("f1");
d[3] = rs.getDouble("f1");
d[4] = rs.getDouble("f1");
d[5] = rs.getDouble("f1");
d[6] = rs.getDouble("f1");
d[7] = rs.getDouble("f1");
d[8] = rs.getDouble("f1");
d[9] = rs.getDouble("f1");
d[10] = rs.getDouble("f1");
d[11] = rs.getDouble("f1");
d[12] = rs.getDouble("f1");
d[13] = rs.getDouble("f1");
d[14] = rs.getDouble("f1");
d[15] = rs.getDouble("f1");
d[16] = rs.getDouble("f1");
d[17] = rs.getDouble("f1");
d[18] = rs.getDouble("f1");
d[19] = rs.getDouble("f1");
d[20] = rs.getDouble("f1");
d[21] = rs.getDouble("f1");
d[22] = rs.getDouble("f1");
d[23] = rs.getDouble("f1");
d[24] = rs.getDouble("f1");
d[25] = rs.getDouble("f1");
d[26] = (double) rs.getInt("label");
samples.add(d);
}
rs.close();
stmt.close();
c.close();
randomforest = new RandomForest(50, 4);
randomforest.createForest(samples);
} catch (Exception e) {
e.printStackTrace();
System.exit(0);
}
System.out.println("-----------------");
try {
// 实例化ObjectOutputStream对象
/*ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream(App.class.getClassLoader().getResource("RandomForest").getFile()));*/
ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream("conf/RandomForest"));
// 将对象写入文件
oos.writeObject(randomforest);
oos.flush();
oos.close();
// 实例化ObjectInputStream对象
/*ObjectInputStream ois = new ObjectInputStream(App.class.getResourceAsStream("RandomForest"));*/
ObjectInputStream ois = new ObjectInputStream(new FileInputStream("conf/RandomForest"));
try {
// 读取对象people,反序列化
RandomForest randomForest = (RandomForest) ois.readObject();
double[] data = new double[samples.get(0).length];
int sum = samples.size();
int right = 0;
for (Double[] sample : samples) {
for (int i = 0; i < sample.length; i++) {
data[i] = sample[i];
}
if (randomForest.predictType(data) == (int) data[26]) {
right++;
}
}
double accurancy = right * 1.0 / sum;
System.out.println("RandomForest Accurancy:" + accurancy);
} catch (ClassNotFoundException e) {
e.printStackTrace();
}
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
